Last updated on
Company health
Ratings
Pepperdata Capacity Optimizer description
Pepperdata Capacity Optimizer is a cloud cost management tool that helps businesses using Spark workloads on Amazon EMR and EKS save money. It works by optimizing resource use in real-time, eliminating wasteful spending on unnecessary cloud capacity. This means your Spark applications run more efficiently and you only pay for what you actually use. Pepperdata Capacity Optimizer operates automatically and boasts an average cost saving of 30-47% for its users.
Who is Pepperdata Capacity Optimizer best for
Pepperdata Capacity Optimizer helps large software and IT companies cut Spark cloud costs on Amazon EMR and EKS by 30-47%. Users praise its clear dashboards, insightful metrics, and cost savings. Some find initial setup complex and desire more automated recommendations.
-
Ideal for large enterprises using Spark on Amazon EMR or EKS.
-
Best suited for software and IT companies seeking cloud cost optimization.
Pepperdata Capacity Optimizer features
| Supported Capacity Optimizer optimizes costs automatically without providing recommendations. |
| Supported Pepperdata Capacity Optimizer optimizes cloud costs by providing real-time insights into resource utilization. |
| Supported Capacity Optimizer maximizes resource utilization and improves performance through automated tuning. |
Pepperdata Capacity Optimizer reviews
We've summarised 39 Pepperdata Capacity Optimizer reviews (Pepperdata Capacity Optimizer G2 reviews) and summarised the main points below.
- Easy installation and great dashboards.
- Significant cost savings.
- Top-notch support.
- Clear, uncluttered dashboards and metrics.
- Highly customizable metrics; valuable job information.
- Excellent visualizations of infrastructure capacity.
- Helps understand and optimize ETL job performance.
- Actionable metrics on user jobs and queries.
- Real-time data display; logical performance data presentation.
- Useful stats, easy to use.
- Provides Spark logs, small file alerts, job recommendations.
- Effective Capacity Optimizer; reduces compute costs.
- Easy root cause identification; responsive support; Spark workload tuning.
- Usage and cost reporting; helpful user interface.
- Insightful details and helpful metrics for cluster performance monitoring.
- Cost and usage monitoring for Hadoop resources.
- Needs fine tuning multiple times; automation for recommendations desired.
- Limited application support.
- Accuracy issues with higher time intervals.
- Difficult setup on new nodes.
- Vague MapR feedback.
- Complicated installation with static components.
- Expensive.
- Lacks data security options.
- Slow data collection and UI delays.
- Less user-friendly interface.
- Log filters are inefficient for large logs.
- Difficult initial configuration.
Pepperdata Capacity Optimizer alternatives
ZestyBetter fit for small to medium businesses. Has broader cloud platform support beyond Spark and EMR. More website traffic momentum.Read more
ProsperOpsBetter for companies of all sizes, including small businesses. Supports AWS, Azure, and Google Cloud, not just Amazon EMR and EKS. Has faster employee growth momentum.Read more
GoodDataBetter for broader industry applications. More user-friendly for creating reports and dashboards. Has more momentum based on website traffic growth.Read more
CAST AIBetter suited for companies using Kubernetes. Focuses on automated cost optimization through real-time resource adjustments and spot instance utilization. Has broader cloud platform compatibility but lacks Spark-specific optimizations. Shows more momentum.Read more
KionBetter for compliance and security management across multiple cloud platforms. Broader cloud platform support (AWS, Azure, GCP). Caters to larger enterprises with complex cloud setups. Has higher ratings, but less momentum.Read more
Tungsten ReadSoft InvoicesFocuses on automating accounts payable processes, unlike Pepperdata Capacity Optimizer, a cloud cost optimization tool for Spark. It has significantly more momentum but Pepperdata Capacity Optimizer is a better fit for small businesses. Tungsten ReadSoft Invoices is a strong competitor and alternative for mid-size and large enterprises.Read more
Pepperdata Capacity Optimizer FAQ
What is Pepperdata Capacity Optimizer and what does Pepperdata Capacity Optimizer do?
Pepperdata Capacity Optimizer is a cloud cost optimization tool specifically designed for Spark workloads on Amazon EMR and EKS. It automatically optimizes resource use in real-time, leading to significant cost savings by eliminating unnecessary cloud spending. Users typically experience cost reductions of 30-47%.
How does Pepperdata Capacity Optimizer integrate with other tools?
Pepperdata Capacity Optimizer integrates seamlessly with Amazon EMR and EKS, focusing on optimizing Spark workloads. It automates resource allocation and tuning in real-time, eliminating the need for manual intervention or other tool integrations.
What the main competitors of Pepperdata Capacity Optimizer?
Alternatives to Pepperdata Capacity Optimizer include Zesty, ProsperOps, and CAST AI. These platforms offer automated cloud cost optimization, resource management, and Kubernetes cost savings, respectively. They provide similar functionalities for businesses seeking to reduce cloud spending.
Is Pepperdata Capacity Optimizer legit?
Pepperdata Capacity Optimizer is a legitimate cloud cost optimization tool for Spark workloads on Amazon EMR and EKS. It automates resource use and boasts average savings of 30-47%, making it a safe and potentially cost-effective solution.
How much does Pepperdata Capacity Optimizer cost?
I couldn't find pricing details for Pepperdata Capacity Optimizer. Contact Pepperdata directly to discuss pricing and determine if Capacity Optimizer is worth the investment for your needs.
Is Pepperdata Capacity Optimizer customer service good?
Customers praise Pepperdata Capacity Optimizer's top-notch support, highlighting the team's responsiveness and dedication to helping users maximize the product's benefits. Users mention easy root cause identification and effective Spark workload tuning with assistance from the support team.
Reviewed by
Michal has worked at startups for many years and writes about topics relating to software selection and IT management. As a former consultant for Bain, a business advisory company, he also knows how to understand needs of any business and find solutions to its problems.
Tymon is a seasoned CTO who loves finding the perfect tools for any task. He recently headed up the tech department at Batmaid, a well-known Swiss company, where he managed about 60 software purchases, including CX, HR, Payroll, Marketing automation and various developer tools.